Multiuav Mission Coordination Based On Swarm Intelligence Algorithm

With the development of science and technology,the future battlefield environment will become increasingly complex and changeable,a single drone has been unable to meet the needs of future battlefields.But mufti-UAV coordination can precisely compensate for the inadequacies of stand-alone aircraft,through the cooperation of multiple drones,the types of tasks that can be accomplished are more and more complex and arduous.Drone cooperation is usually composed of two parts:task allocation and route planning.Complete as many tasks as possible with minimal resource costs,which is one of the difficulties in solving the multi-task problem of multiple drones.The route planning is to find the optimal or sub-optimal route from the base to each mission to complete the mission and return to the base,based on the completion of the task assignment,which is similar to the famous travel business,one of the keys to the realization of the autonomous drones task.This topic studies the route planning of UAV coordination and proposes corresponding improvement strategies to improve the efficiency of route planning.The paper mainly completes the following points:Firstly,the principle and model of task assignment and path planning are introduced,for MUAVs,the specific problems of N target points are modeled and solved.The problem is divided into two parts:task allocation and path planning.In the task planning process,using the idea of K-means clustering,the target point is divided into several areas is the first step.Then make path planning for each area.Next the path planning is converted into a famous traveling salesman problem to solve.Finally,the unmanned aircraft coordination system framework is given.Secondly,we discretize the original brainstorming optimization algorithm to solve traveling salesman problems in order to optimize the path planning.In the process of initializing the population,the access order of the city is taken as the coding of each individual,and the Hamming distance is used as a clustering operation basis in place of the original Euclidean distance.In the process of mutation,the method of adding random values into the original algorithm is transformed into randomly selecting two nodes and exchanging the elements on the nodes.From the optimization results,we can see that the proposed method has little difference with other improved algorithms,indicating that this algorithm has a good application prospect.Thirdly,in order to better solve the problem of path planning which is similar to the traveling salesman problem,the basic discrete brainstorming optimization algorithm is improved based on the third chapter.In the initialization process,an initial population is a better solution that using a heuristic algorithm which can construct a good TSP path,and is optimized by optimization algorithm.The clustering operation in the decision-making space is transferred to the target space,the multi-dimensional distance solution is converted into a one-dimensional distance solving problem,which greatly reduces the computational complexity and saves a lot of time.The improved algorithm is applied to the traveling salesman problem,from the simulation results,it can be seen that improved algorithm not only improves the convergence,but also greatly accelerate the speed of the algorithm,which making overall performance significantly improved.Finally,considering the algorithm is applied to cooperative reconnaissance missions of multi-UAV,so the concept of layering is introduced.all point in the first will be a target group as a whole and obtain the shortest scheme of retention time in UAV cruise all the target group.Then the path between each target point is further optimized in the target group,and the minimum resource allocation and minimum retention time of the reconnaissance mission are obtained.According to the change of the coordinates of the drone over time,the distance between the two drones of the same base is obtained,and the drone from the same base only needs one relay drone to complete the communication task.